Monday, 25 May 2015

Ahead of the game

In Vincent Granville PhD's book Developing Analytical Talent: Becoming a Data Scientist he writes an interesting section on the history and pioneers of data science. He highlights past developments and predicts what will happen in the future. I quote from his book.
  • "1988: Artificial intelligence. Also: computational statistics, data analysis, pattern recognition and rule systems.
  • 1995: Web analytics. Also: machine learning, business intelligence, data mining, ROI, distributed architecture, data architecture, quant, decision science, knowledge management and information science.
  • 2003: Business analytics. Also: text mining, unstructured data, semantic web, Natural Language Processing (NLP), Key Performance Indicator (KPI), predictive modeling, cloud computing, lift, yield, NoSQL, Business Intelligence (BI), real-time analytics, collaborative filtering, recommendation engines and mobile analytics.
  • 2012: Data Science. Also: big data, analytics, software as a service (SaaS), on-demand analytics, digital analytics, Hadoop, NewSQL, in-memory analytics, machine-to-machine, sensor data, healthcare analytics, utilities analytics, data governance and in-column databases.
  • 2022: Data engineering. Also: analytics engineering, data management, data shaping, art of optimization, optimization science, optimization engineering, business optimization and data intelligence."
After I've read this I realized that Autolytix Data Science is ahead of the game. For the past 5 years we have been working on solving optimization problems, which Granville notes will only be available in 2022.

Optimization in any subject matter can be difficult, but our approach was to build the gaps between analytics and profitability.  

In order to bridge this gap we developed what we call the data science maturity curve, to start understanding the link between data and profits.

The maturity curve was a good start, but we still needed a link between the analytics and profits. This is how we solved it.

In order to make the analytics work for you in your business, you need to quantify the impact a change in the variables may have on the business. For example: if you spend $1000 per month on
stationary versus $100,000 on raw materials, a 10% change in both these expenses will have a significantly different impact on your bottom line. This is where prioritization will come into play. You will prioritize a 10% saving on the $100,000 raw materials above that of stationary.
To execute this saving, you will need to plan for this change and we use a strategic initiative to assess the variables that need to change and how it will be changed to affect the result you require.
For example: In a strategic initiative we will recommend which suppliers to eliminate and/or which suppliers need a pricing review, to renegotiate contract pricing. There are many ways and means to affect this change.
Last step will be to implement this change. Lastly, when drafting your strategic initiative, also be cost conscious. Sometimes, it will cost you more than the benefit you will receive.

I hope this short article has given you some idea of how to turn data into profits.

High Performance Fleet Program

For all fleet owners, Autolytix Data Science developed a High Performance Fleet Program, specifically focused to drastically reduce fleet cost and substantially increase your profitability.

Visit our website to learn more about this program.

Click Here to visit the High Performance Fleet Program

Autolytix Data Science New Website

It has been a while since I last made a post, but it's been for good reason. At Autolytix Data Science we are currently developing a bunch of great new products. I will keep you posted in due course.

I would however like to invite you to visit our new website

We will expand on the content of the website in the months to come. Any feedback on the site is very welcome.

Monday, 14 July 2014

What every business needs

Effective operational execution is a function of three key elements, namely a system, people and process. These essential elements are the building blocks for every business as well as every function within a company. It doesn't matter whether you work in supply chain, finance, human resources or procurement, these three elements holds the key to greater execution.

Greater execution means better performance and a happier boss, but in order to achieve this the system, people and processes need to be aligned and work in harmony. 

Implementing a new system on the premise that it will solve all the company's problems is a mistake that is often made in companies today. Implementing a new business intelligence application will not solve the company's problems if people and processes are not aligned with the system. A system can't function on its own. It needs people to use it actively on a daily basis and it needs process to control how, what, when and why it is used.

A system will allow people to control the flow of information within the company. Without a system the data will be random and to make informed business decisions will be difficult. In order to harness the data the company generates a system must be in place. The system can be as simple as an Excel spreadsheet or a basic accounting system or as advanced as SAP or other applications. The system is an essential part of every day business, but without people and process, the system will fail. 

People are needed to inform the system, but the influx of data cannot be unstructured and uncontrolled. If people are left to decide for themselves how, when and if they should use the system, they generally tend not to embrace the system. People are comfortable with how they do things. Change, especially a new system normally creates discomfort and resistance to change is evident in almost every company. 

Process enforces compliance. People will tend not to embrace the implementation of a new system. In order to achieve the desired results from the system, a defined process must be enforced. If the process lacks details and specifics and is open for interpretation is will also fail. Be very specific when implementing a new process. Define exactly what the user must be doing on a daily basis, how they should be doing it, when the task must be complete and also give them the necessary context of why it is important. 

Sooner than later people will get accustomed to the new process and system and they will deliver the results. 

In conclusion, if the system, people and process is aligned, the benefits will far exceed the cost of the implementation, but if they are not aligned it is likely to fail. 

  • Because, the process defines how the system should be used the data is consistent, accurate and on-time.
  • The data is ready to be used for further analysis, leading to more insight.
  • Improved insight will lead to better decisions in the future.
  • People will be happier and more productive, because they will know exactly what the expectations are for the system and what they must deliver on a daily basis. 
  • A successful project implementation with a system working as intended.
The system, people and process is not all the business requires to succeed, but it is three of the fundamental building blocks for success.


Jeane-Louis's 40th Birthday

It was a special night to celebrate Jeane-Louis's 40th birthday. Jeane-Louis we hope you enjoyed the party as much as we did. We hope the next 40 years will be full of success, love and happiness. Here's some pics of the party. Enjoy.

Gatsby night with Madelein Knox

We recently celebrated Madelein Knox's 40th birthday. It was a fantastic evening spent with great friends. Madelein we wish you a very happy 40th and hope the next 40 will be very special. Here are some pictures of the party.

Thursday, 10 July 2014

What McKinsey has to say about Big Data

I really like McKinsey's views on big data. Big data will become just as important as any other function in a company. This is a very informative report. You can download it from the following link.

McKinsey Report - Big Data: The next frontier for innovation, competition and productivity